PromptTemplateConfig Class

Configuration for a prompt template.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Inheritance

KernelBaseModel

PromptTemplateConfig

Constructor

PromptTemplateConfig(*, name: str = '', description: str | None = '', template: str | None = None, template_format: Literal['semantic-kernel', 'handlebars', 'jinja2'] = 'semantic-kernel', input_variables: list[InputVariable] = None, allow_dangerously_set_content: bool = False, execution_settings: dict[str, PromptExecutionSettings] = None)

Parameters

Name	Description
name Required	The name of the prompt template.
description Required	The description of the prompt template.
template Required	The template for the prompt.
template_format Required	The format of the template, should be 'semantic-kernel', 'jinja2' or 'handlebars'.
input_variables Required	The input variables for the prompt.
allow_dangerously_set_content Required	<xref:<xref:semantic_kernel.prompt_template.prompt_template_config.bool = False>> Allow content without encoding throughout, this overrides the same settings in the prompt template config and input variables. This reverts the behavior to unencoded input.
execution_settings Required	The execution settings for the prompt.

Keyword-Only Parameters

Name	Description
name Required
description Required
template Required
template_format	Default value: semantic-kernel
input_variables Required
allow_dangerously_set_content Required
execution_settings Required

Methods

add_execution_settings	Add execution settings to the prompt template.
check_input_variables	Verify that input variable default values are string only.
from_json	Create a PromptTemplateConfig instance from a JSON string.
get_kernel_parameter_metadata	Get the kernel parameter metadata for the input variables.
restore	Restore a PromptTemplateConfig instance from the specified parameters.
rewrite_execution_settings	Rewrite execution settings to a dictionary.

add_execution_settings

Add execution settings to the prompt template.

add_execution_settings(settings: PromptExecutionSettings, overwrite: bool = True) -> None

Parameters

Name	Description
settings Required
overwrite	Default value: True

check_input_variables

Verify that input variable default values are string only.

check_input_variables()

from_json

Create a PromptTemplateConfig instance from a JSON string.

from_json(json_str: str) -> PromptTemplateConfig

Parameters

Name	Description
json_str Required

get_kernel_parameter_metadata

Get the kernel parameter metadata for the input variables.

get_kernel_parameter_metadata() -> list[KernelParameterMetadata]

restore

Restore a PromptTemplateConfig instance from the specified parameters.

restore(name: str, description: str, template: str, template_format: Literal['semantic-kernel', 'handlebars', 'jinja2'] = 'semantic-kernel', input_variables: list[InputVariable] = [], execution_settings: dict[str, PromptExecutionSettings] = {}, allow_dangerously_set_content: bool = False) -> PromptTemplateConfig

Parameters

Name	Description
name Required	The name of the prompt template.
description Required	The description of the prompt template.
template Required	The template for the prompt.
template_format	The format of the template, should be 'semantic-kernel', 'jinja2' or 'handlebars'. Default value: semantic-kernel
input_variables	The input variables for the prompt. Default value: []
execution_settings	The execution settings for the prompt. Default value: {}
allow_dangerously_set_content	Allow content without encoding. Default value: False

Returns

Type	Description
	A new PromptTemplateConfig instance.

rewrite_execution_settings

Rewrite execution settings to a dictionary.

rewrite_execution_settings(settings: None | PromptExecutionSettings | list[PromptExecutionSettings] | dict[str, PromptExecutionSettings]) -> dict[str, PromptExecutionSettings]

Parameters

Name	Description
settings Required

Attributes

model_computed_fields

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'populate_by_name': True, 'validate_assignment': True}

model_fields

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.fields from Pydantic V1.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'allow_dangerously_set_content': FieldInfo(annotation=bool, required=False, default=False), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=''), 'execution_settings': FieldInfo(annotation=dict[str, PromptExecutionSettings], required=False, default_factory=dict), 'input_variables': FieldInfo(annotation=list[InputVariable], required=False, default_factory=list), 'name': FieldInfo(annotation=str, required=False, default=''), 'template': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'template_format': FieldInfo(annotation=Literal['semantic-kernel', 'handlebars', 'jinja2'], required=False, default='semantic-kernel')}

allow_dangerously_set_content

allow_dangerously_set_content: bool

description

description: str | None

execution_settings

execution_settings: dict[str, PromptExecutionSettings]

input_variables

input_variables: list[InputVariable]

name

name: str

template

template: str | None

template_format

template_format: Literal['semantic-kernel', 'handlebars', 'jinja2']